论文标题
关于使用基于序言的探索改善多通道Aloha的吞吐量
On Improving Throughput of Multichannel ALOHA using Preamble-based Exploration
论文作者
论文摘要
已经对机器型通信（MTC）进行了广泛的研究，以提供有关设备和传感器（IoT）中的传感器的连接性。由于稀疏活动，随机访问，例如Aloha，用于MTC降低信号开销。 In this paper, we propose to adopt exploration for multichannel ALOHA by transmitting preambles before transmitting data packets in MTC, and show that the maximum throughput can be improved by a factor of 2 - exp(-1) = 1.632, In the proposed approach, a base station (BS) needs to send the feedback information to active users to inform the numbers of transmitted preambles in multiple channels, which can be reliably estimated as in compressive random 使用权。还通过快速重审进行稳态分析，这表明数据包碰撞的概率变得较低，因此，对于较轻的系统，延迟中断概率大大降低了。仿真结果还证实了分析的结果。
Machine-type communication (MTC) has been extensively studied to provide connectivity for devices and sensors in the Internet-of-Thing (IoT). Thanks to the sparse activity, random access, e.g., ALOHA, is employed for MTC to lower signaling overhead. In this paper, we propose to adopt exploration for multichannel ALOHA by transmitting preambles before transmitting data packets in MTC, and show that the maximum throughput can be improved by a factor of 2 - exp(-1) = 1.632, In the proposed approach, a base station (BS) needs to send the feedback information to active users to inform the numbers of transmitted preambles in multiple channels, which can be reliably estimated as in compressive random access. A steady-state analysis is also performed with fast retrial, which shows that the probability of packet collision becomes lower and, as a result, the delay outage probability is greatly reduced for a lightly loaded system. Simulation results also confirm the results from analysis.
